This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
2009 WRI World Congress on Computer Science and Information Engineering
A Robust Approach of Sonar Image Feature Detection and Matching
Los Angeles, California USA
March 31-April 02
ISBN: 978-0-7695-3507-4
This paper is concerned with Modulus Maximum of Wavelet Transform (MMWT) and a graph theoretic method. The methods are applicable to extracting features of seafloor sonar image and data association problems. We will first get image’s modulus and modulus’ direction matrix by MMWT method. And according to calculating modulus’ threshold, obtain the geometric features of the image or the point features. Then calculate geometric centrobaric coordinate of the geometric features as matching point.For point feature, feature’s Vector will be created by the combination of region direction of modulus. For geometric feature, feature’s Vector is its perimeter and area information. At last, the key points between images will be associated by Maximum Common Subgraph method and validated by the feature vectors. The experimental results show that the methods are reliable and robust in continuous sonar image of seafloor.
Index Terms:
Sonar Image Feature, MMWT, Maximum Common Subgraph, Matching
Citation:
Shoudong Shi, Demin Xu, "A Robust Approach of Sonar Image Feature Detection and Matching," csie, vol. 6, pp.523-527, 2009 WRI World Congress on Computer Science and Information Engineering, 2009
Usage of this product signifies your acceptance of the Terms of Use.